# Agentic RAG, agents and memory

Area: [Retrieval-augmented generation](https://mlsanity.com/rag/index.md). HTML: https://mlsanity.com/rag/agentic-rag-agents-and-memory/

## Key facts

- Agentic RAG, agents and memory: 449 papers on arXiv since 2022 (data through 7 Oct 2026).
- 47 of its 449 mapped papers (10%) cite “Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG” (2025, arXiv 2501.09136).
- 12 of its 449 mapped papers (3%) cite “RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement” (2024, arXiv 2412.12881).
- 15 new papers 17 Sep–7 Oct.

## Most cited here

- [Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG](https://mlsanity.com/paper/2501.09136/) (2025), cited by 47 papers here
- [RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement](https://mlsanity.com/paper/2412.12881/) (2024), cited by 12 papers here
- [Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning](https://mlsanity.com/paper/2505.14069/) (2025), cited by 12 papers here
- [PaperQA: Retrieval-Augmented Generative Agent for Scientific Research](https://mlsanity.com/paper/2312.07559/) (2023), cited by 9 papers here
- [RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation](https://mlsanity.com/paper/2403.05313/) (2024), cited by 8 papers here
- [ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding](https://mlsanity.com/paper/2501.07861/) (2025), cited by 8 papers here
- [s3: You Don't Need That Much Data to Train a Search Agent via RL](https://mlsanity.com/paper/2505.14146/) (2025), cited by 8 papers here
- [MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation](https://mlsanity.com/paper/2501.00332/) (2024), cited by 7 papers here
- [MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning](https://mlsanity.com/paper/2505.20096/) (2025), cited by 7 papers here
- [LeanDojo: Theorem Proving with Retrieval-Augmented Language Models](https://mlsanity.com/paper/2306.15626/) (2023), cited by 6 papers here

## New (17 Sep–7 Oct)

- [The Attribution Blind Spot: Layerwise Trajectory Diagnostics for Source Reliance in Retrieval-Augmented Language Models](https://mlsanity.com/paper/2610.09493/) (2026-10-07)
- [Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents](https://mlsanity.com/paper/2610.08452/) (2026-10-06)
- [Agentic RAG Evaluation: Budget Allocation Across Questions, Trajectories, and Reads](https://mlsanity.com/paper/2610.05034/) (2026-10-04)
- [Retrieval-Augmented Large Language Model Decision-Making for Autonomous Driving Guided by Chinese Philosophical Wisdom](https://mlsanity.com/paper/2610.03948/) (2026-10-02)
- [Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation](https://mlsanity.com/paper/2610.03136/) (2026-10-02)
- [On-Premises Multi-Course RAG Tutoring for Business Education: Hardware-Software Trade-offs in a Campus AI Tutor](https://mlsanity.com/paper/2610.02510/) (2026-10-01)
- [Conversational Capture: A Trajectory-Level Framework for Evaluating Generative Engine Optimization in Multi-turn Human-Agent Interaction](https://mlsanity.com/paper/2609.40069/) (2026-09-30)
- [Retrieval-Augmented Skill Optimization via Cross-Harness Adaptation](https://mlsanity.com/paper/2609.38024/) (2026-09-29)
- [RAGWarrant: Evidence-Preserving Governance for RAG Policy Promotion Under Quality, Cost, Latency, and Risk Constraints](https://mlsanity.com/paper/2609.34179/) (2026-09-28)
- [The Fellowship of the Query: Learning Retrieval Actions](https://mlsanity.com/paper/2609.28653/) (2026-09-23)
- [Knowledge-as-Skill: A Structural Design for Autonomous Knowledge-Base Use by LLM Agents](https://mlsanity.com/paper/2609.25991/) (2026-09-22)
- [From Lexical Baselines to Agentic Retrieval-Augmented Generation: Structured Skill and Responsibility-Level Extraction with the SFIA Framework](https://mlsanity.com/paper/2609.35806/) (2026-09-19)
- [Attributable Post-Rationalization in RAG Citations: A Controlled Reproduction and an RLVR Comparison](https://mlsanity.com/paper/2609.23053/) (2026-09-19)
- [Semantics Delivery Network: Rethinking Web Retrieval Infrastructure for LLM Agents](https://mlsanity.com/paper/2609.22486/) (2026-09-18)
- [RAFT: A Stateful Retrieval-Augmented Framework for Troubleshooting Agents](https://mlsanity.com/paper/2609.20754/) (2026-09-17)